As complex structures are extracted from input data sets, the practice of data mining is challenged with keeping analysts closer to the data exploration process to reveal powerful insight upon which business owners can directly act. For example, existing clickpath mining methods have focused on reporting top clickpaths, sequential patterns, and funnel analyses from input clickstreams. As powerful as such clickpath mining methods may be, they often lead to huge, incomprehensible, and non-interesting result sets. Most existing business intelligence products have not attempted to address the problem of clickpath visualization. Of the existing business intelligence products that address the problem of clickpath visualization, most of the products present massive cross-weaving web graphs or multi-directed graphs. Unfortunately, this type of structure becomes too complex to analyze and mine as the number of clickpaths increases. These challenges stress the importance of an interactive and visual representation of clickpath mining results. In addition, these challenges underscore the importance of a visual representation of funnels to more easily absorb mined results and provide visual impact for business action. For example, understanding how users navigate web sites helps site designers improve site design to provide a better user experience. Existing clickpath mining methods do not easily lend themselves to providing powerful insight into how users traverse sites. This makes it difficult for site designers to both understand and take action on the results.
For these reasons, a system for visually mining sequentially ordered data is desired to address one or more of these and other disadvantages.